Analysis of Bacterial metabarcoding sequencing results
1
Base data
1.1
OTU table
1.2
Taxonomy table
1.3
Experimental design
2
Descriptive statistics
2.1
List of the 50th most abundant bacterial OTU’s
2.2
Plot the 50th most abundant bacterial OTU’s
2.3
Test the sampling effetiveness using Hill number of order 0 (q0)
2.3.1
List diversity estimates for all sampling group
2.3.2
List and ploting diversity estimates by group
2.4
Explore the samplings relationship (Principal Coordinates Analysis - PCoA)
3
Comparative statistics
3.1
Test the statistical significance among the group’s species composition
3.2
Identify differential abundant bacterial OTUs with edger
3.2.1
Filter original dataset to include only OTU’s with at last 3 observations
3.2.2
Get estimates of the bacterial OTU’s differential abundance
3.2.3
Get the total number of differentially abundant bacterial OTUs at FDR < 0:05
3.2.4
Plot the tagwise log-fold-changes against log-cpm
1
Base data
1.1
OTU table
1.2
Taxonomy table
1.3
Experimental design
2
Descriptive statistics
2.1
List of the 50th most abundant bacterial OTU’s
2.2
Plot the 50th most abundant bacterial OTU’s
2.3
Test the sampling effetiveness using Hill number of order 0 (q0)
2.3.1
List diversity estimates for all sampling group
2.3.2
List and ploting diversity estimates by group
2.3.2.1
Sample effectiveness of Early group
2.3.2.2
Sample effectiveness of Late group
2.4
Explore the samplings relationship (Principal Coordinates Analysis - PCoA)
3
Comparative statistics
3.1
Test the statistical significance among the group’s species composition
3.2
Identify differential abundant bacterial OTUs with edger
3.2.1
Filter original dataset to include only OTU’s with at last 3 observations
3.2.2
Get estimates of the bacterial OTU’s differential abundance
## Disp = 0.49192 , BCV = 0.7014
3.2.3
Get the total number of differentially abundant bacterial OTUs at FDR < 0:05
3.2.4
Plot the tagwise log-fold-changes against log-cpm